Performance Enhancement of Consumer-Grade MEMS Sensors through Geometrical Redundancy
Open Access
- 16 July 2021
- Vol. 21 (14), 4851
- https://doi.org/10.3390/s21144851
Abstract
The paper deals with performance enhancement of low-cost, consumer-grade inertial sensors realized by means of Micro Electro-Mechanical Systems (MEMS) technology. Focusing their attention on the reduction of bias instability and random walk-driven drift of cost-effective MEMS accelerometers and gyroscopes, the authors hereinafter propose a suitable method, based on a redundant configuration and complemented with a proper measurement procedure, to improve the performance of low-cost, consumer-grade MEMS sensors. The performance of the method is assessed by means of an adequate prototype and compared with that assured by a commercial, expensive, tactical-grade MEMS inertial measurement unit, taken as reference. Obtained results highlight the promising reliability and efficacy of the method in estimating position, velocity, and attitude of vehicles; in particular, bias instability and random walk reduction greater than 25% is, in fact, experienced. Moreover, differences as low as 0.025 rad and 0.89 m are obtained when comparing position and attitude estimates provided by the prototype and those granted by the tactical-grade MEMS IMU.Keywords
This publication has 28 references indexed in Scilit:
- Gyroscope Technology and Applications: A Review in the Industrial PerspectiveSensors, 2017
- North Finding System using Multi-Position Method with a 2-Axis Rotray Table for a MortarIEEE Sensors Journal, 2016
- The Human Element and Autonomous ShipsTransNav, the International Journal on Marine Navigation and Safety of Sea Transportation, 2016
- Principles of GNSS, inertial, and multisensor integrated navigation systems, 2nd edition [Book review]IEEE Aerospace and Electronic Systems Magazine, 2015
- A Novel Optimal Configuration form Redundant MEMS Inertial Sensors Based on the Orthogonal Rotation MethodSensors, 2014
- Fast Thermal Calibration of Low-Grade Inertial Sensors and Inertial Measurement UnitsSensors, 2013
- IntroductionAdvances in Industrial Control, 2011
- A Systematic Approach for Extended Kalman Filter Tuning and Low-Cost Inertial Sensor Calibration within a GPS/INS ApplicationPublished by American Institute of Aeronautics and Astronautics (AIAA) ,2010
- Aircraft Attitude, Position, and Velocity Determination Using Sensor FusionPublished by American Institute of Aeronautics and Astronautics (AIAA) ,2008
- A Least Squares Estimate of Satellite AttitudeSIAM Review, 1965